Improved stochastic synchronization criterion of delayed Markovian coupled neural networks with random coupling strengths and partial information on transition probabilities

This paper investigates the synchronization problem of delayed Markovian coupled neural networks with random coupling strengths and partial information on transition probabilities. In this coupled neural network model, each transition rate is only known partial information, and the coupling strengths are characterized by mutually independent random variables. By constructing a new augmented Lyapunov-Krasovskii functional (LKF) and reciprocal convex combination, synchronization criterion is derived. In comparison with existing results, the established criterion is not only less conservative but with less computational burden. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed criterion.